Spectral Bands Research Articles

Electro-Clinical Features and Functional Connectivity Analysis in SYN1-Related Epilepsy.

There is currently scarce data on the electroclinical characteristics of epilepsy associated with synapsin 1 (SYN1) pathogenic variations. We examined clinical and electro-encephalographic (EEG) features in patients with epilepsy and SYN1 variants, with the aim of identifying a distinctive electroclinical pattern. In this retrospective multicenter study, we collected and reviewed demographic, genetic, and epilepsy data of 19 male patients with SYN1 variants. Specifically, we analyzed interictal EEG data for all patients, and electro-clinical data from 10 epileptic seizures in 5 patients, using prolonged video-EEG monitoring recordings. Inter-ictal EEG functional connectivity parameters and frequency spectrum of the 10 patients over 12 years of age, were computed and compared with those of 56 age- and sex-matched controls. The main electroclinical features of epilepsy in patients with SYN1 were (1) EEG background and organization mainly normal; (2) interictal abnormalities are often rare or not visible on EEG; (3) more than 60% of patients had reflex seizures (cutaneous contact with water and defecation being the main triggers) isolated or associated with spontaneous seizures; (4) electro-clinical semiology of seizures was mainly temporal or temporo-insulo/perisylvian with a notable autonomic component; and (5) ictal EEG showed a characteristic rhythmic theta/delta activity predominating in temporo-perisylvian regions at the beginning of most seizures. Comparing patients with SYN1 to healthy subjects, we observed a shift to lower frequency bands in power spectrum of interictal EEG and an increased connectivity in both temporal regions. A distinct epilepsy syndrome emerges in patients with SYN1, with a rather characteristic clinical and EEG pattern suggesting predominant temporo-insular involvement. ANN NEUROL 2024.

Superhydrophobic Composite Coatings Can Achieve Durability and Efficient Radiative Cooling of Energy-Saving Buildings.

Passive daytime radiative cooling (PDRC) technology has received a great deal of attention in the field of energy efficiency and environmental protection as a sustainable technology and a large-scale and promising solution to mitigate the environmental impact of global warming. In this study, we prepared PDRC material by combining FEP with modified Al2O3 particles and using the method of spray combined with phase separation. The synergistic effect of the formed surface micronanostructures, combined with the molecular vibration of FEP and the phonon polarization resonance of Al2O3, further improves the optical performance of the PDRC coating. The PDRC coating has an average reflectivity of 0.96 in the solar spectral band (0.3-2.5 μm) and an average emissivity of 0.963 in the atmospheric window band ((8-13 μm). In addition, the PDRC coating had good hydrophobicity, and its water contact angle (WAC) reached 159.3°. Under direct sunlight conditions, PDRC materials have a good temperature drop (4.9 °C) compared to ambient temperatures and radiative cooling power (81.2 W/m2). The prepared coating maintains superhydrophobicity and excellent cooling performance when soaked in solutions of different pH values and UV radiation, which was of great significance for sustainable applications. Our work provides a form of long-term cooling that can be effectively implemented in green and energy-efficient buildings.

Allethrin and tetramethrin molecular adsorption on novel phosphoaluminane nanosheet based on first-principles investigation

Allethrin and tetramethrin are both active ingredients in the production of insect spray. Being very toxic in nature, the inhalation of allethrin and tetramethrin causes various side effects in human beings. For the detection of allethrin and tetramethrin, the effectiveness of the base material phosphoaluminane is studied in the current work with the help of the density functional theory (DFT) calculations. The stability of phosphoaluminane is ensured with the support of formation energy and phonon band spectrum. The electronic properties of phosphoaluminane are systematically investigated using band structure and projected density of states (PDOS) maps. The obtained band gap value of phosphoaluminane is 1.716 eV, which confirms that the base material has semiconducting properties. The adsorption behaviour of target molecules allethrin and tetramethrin on phosphoaluminane are explored with prominent parameters including adsorption energy, Mulliken population analysis, and relative band gap changes. The adsorption energy range is recorded to be in the scope of −0.237 eV to −0.597 eV. From the results, it is clear that both allethrin and tetramethrin are physisorbed on phosphoaluminane sheets. Hence, novel phosphoaluminane nanosheets can be utilised as a sensing material for allethrin and tetramethrin.

ChromaFlash: Snapshot Hyperspectral Imaging Using Rolling Shutter Cameras

Hyperspectral imaging captures scene information across narrow, contiguous bands of the electromagnetic spectrum. Despite its proven utility in industrial and biomedical applications, its ubiquity has been limited by bulky form factors, slow capture times, and prohibitive costs. In this work, we propose a generalized approach to snapshot hyperspectral imaging that only requires a standard rolling shutter camera and wavelength-adjustable lighting. The crux of this approach entails using the rolling shutter as a spatiotemporal mask, varying incoming light quicker than the camera's frame rate in order for the captured image to contain rows of pixels illuminated at different wavelengths. An image reconstruction pipeline then converts this coded image into a complete hyperspectral image using sparse optimization. We demonstrate the feasibility of this approach by deploying a low-cost system called ChromaFlash, which uses a smartphone's camera for image acquisition and a series of LEDs to change the scene's illumination. We evaluated ChromaFlash through simulations on two public hyperspectral datasets and assessed its spatial and spectral accuracy across various system parameters. We also tested the real-world performance of our prototype by capturing diverse scenes under varied ambient lighting conditions. In both experiments, ChromaFlash outperformed state-of-the-art techniques that use deep learning to convert RGB images into hyperspectral ones, achieving snapshot performance not demonstrated by prior attempts at accessible hyperspectral imaging.

Vertical Barrier Heterostructures for Reliable and High-Performance Self-Powered Infrared Detection.

With their fascinating properties, emerging two-dimensional (2D) materials offer innovative ways to prepare high-performance infrared (IR) detectors. However, the current performance of 2D IR photodetectors is still below the requirements for practical application owing to the severe interfacial recombination, sharply raised contact resistance, and deteriorated metal conductivity at nanoscale. Here, we introduce a vertical barrier heterojunction with a structure of PtSe2/GaAs that combines the excellent optoelectronic properties of transition metal sulfides with topological semi-metals, which allows for an adjustable bandgap and high carrier mobility. The heterojunction was fabricated using the wet transfer method. The heterostructures show significant rectification behaviors and photovoltaic effects, which allow it to operate as a self-driven photodetector at zero bias. The photoresponse parameters at 850 nm with zero bias voltage are 67.2 mA W-1, 6.7 × 1012 Jones, 9.8%, 3.8 × 105, 164 μs, and 198 μs for the responsivity, specific detectivity, external quantum efficiency, Ilight/Idark ratio, rise time, and fall time, respectively. Moreover, the heterojunction is highly sensitive to a wide spectral band from ultraviolet to near-infrared (360-1550 nm). At the same time, this heterostructure demonstrates significant potential for applications in IR polarized light detection and room-temperature high-resolution IR imaging. The excellent properties of the heterojunction make it well-suited for high-performance, self-powered IR detection.

Assessment of Atmospheric Correction Algorithms for Correcting Sunglint Effects in Sentinel-2 MSI Imagery: A Case Study in Clean Lakes

The Sentinel-2 Multi-Spectral Instrument (MSI) is characterized by short revisit times (5 days), red-edge spectral bands (665 nm and 705 nm), and a high spatial resolution (10 m), making it highly suitable for monitoring water quality in both inland and coastal waters. Unlike SeaWiFS, which can adjust its viewing angles to minimize sunglint, the Sentinel-2 MSI operates with fixed near-nadir angles, which makes it more susceptible to sunglint. Additionally, the complex optical properties of water pose challenges in accurately determining its water-leaving reflectance. Therefore, we compared the effectiveness of six atmospheric correction (AC) algorithms (POLYMER, MUMM, DSF, C2RCC, BP, and GRS) in correcting sunglint using two typical lakes in Xinjiang, China, as examples. The results indicated that POLYMER achieved the highest overall evaluation score (1.61), followed by MUMM (1.21), while BP exhibited the lowest performance (0.62). Specifically, POLYMER showed robust performance at the 665 nm band with RMSE = 0.0012 sr−1, R2 = 0.74, and MAPE = 30.68%, as well as at the 705 nm band with RMSE = 0.0014 sr−1, R2 = 0.42, and MAPE = 38.44%. At the 443, 490, and 560 nm bands, MUMM showed better performance (RMSE ≤ 0.0026 sr−1, R2 ≥ 0.86, MAPE ≤ 28.20%). In terms of band ratios, POLYMER exhibited the highest accuracy (RMSE ≤ 0.093 and MAPE ≤ 22.2%), particularly for the ratio Rrs(490)/Rrs(560) (R2 = 0.71). In general, POLYMER is the best choice for the sunglint correction of Xinjiang’s clean lakes. This study assessed the capability of different AC algorithms for sunglint correction and enhanced the monitoring capability of MSI data in clean waters.

The Development of a Novel Nitrate Portable Measurement System Based on a UV Paired Diode-Photodiode.

Nitrates can cause severe ecological imbalances in aquatic ecosystems, with considerable consequences for human health. Therefore, monitoring this inorganic form of nitrogen is essential for any water quality management structure. This research was conducted to develop a novel Nitrate Portable Measurement System (NPMS) to monitor nitrate concentrations in water samples. NPMS is a reagent-free ultraviolet system developed using low-cost electronic components. Its operation principle is based on the Beer-Lambert law for measuring nitrate concentrations in water samples through light absorption in the spectral range of 295-315 nm. The system is equipped with a ready-to-use ultraviolet sensor, light emission diode (LED), op-amp, microcontroller, liquid crystal display, quartz cuvette, temperature sensor, and battery. All the components are assembled in a 3D-printed enclosure box, which allows a very compact self-contained equipment with high portability, enabling field and near-real-time measurements. The proposed methodology and the developed instrument were used to analyze multiple nitrate standard solutions. The performance was evaluated in comparison to the Nicolet Evolution 300, a classical UV-Vis spectrophotometer. The results demonstrate a strong correlation between the retrieved measurements by both instruments within the investigated spectral band and for concentrations above 5 mg NO3-/L.

Variations in solar irradiance caused by solar cycle affect the temporal stability of ETM+ (LS7) ToA reflectance values at pseudo-invariant calibration sites (PICS)

ABSTRACT The aim of this study is to quantify the impact of the effect of long-term solar cycle variations in solar irradiance on the accuracy and temporal stability of ToA reflectance values from Enhanced Thematic Mapper Plus (ETM+/L7) sensor images. We used 1382 ETM+ scenes corresponding to five Pseudo-Invariant Calibration Sites (PICS), obtained between 2003 and 2020. Solar irradiance data from the Spectral Irradiance Monitor (SIM/SORCE) were used to calculate daily values of mean exoatmospheric solar irradiance (ESUN), implemented in the radiometric correction of ToA reflectance. Enhanced temporal stability coefficients and variance tests were calculated to evaluate the stability of the time series obtained. The results indicate that the use of daily SIM/SORCE solar spectra has a significant impact (alpha <0.001) on radiometric correction and the accuracy of ToA reflectance values. In radiometric calibration, the percentage of top of atmosphere temporal stability that can be recovered based on 5 Sahara PICS ETM+/L7 scenes can exceed 0.75%, 0.50%, 0.39%, 0.45%, 0.30% and 0.25% in the blue, green, red, NIR, SWIR-1 and SWIR-2 spectral bands, respectively, and is not considered statistically significant (alpha >0.05). We concluded that considering the effects of solar cycles during the radiometric calibration of multispectral sensors contributes to improving the long-term stability of ToA reflectance products.

Normalized Difference Red-NIR-SWIR: A new Sentinel-2 three-band spectral index for mapping freshly-opened swiddens in the tropics

Swidden agriculture is undergoing a rapid but overlooked transition and transformation in the tropics, complicating global carbon budgeting and sustainable livelihood assessment of swiddeners. Remotely sensed algorithms for accurately detecting swiddening practices have been slowly developed to generate annual updates on their dynamics. This is primarily because, using medium spatial resolution imagery (≥30 m), it is challenging to identify the exact boundary of swidden patches. Spectral-based approaches have by far dominated the detection and mapping of swidden agriculture, but the potential of Sentinel-2 has not been examined. To reconstruct annual information of swidden agriculture, a new Sentinel-2 three-band spectral index, i.e., the Normalized Difference Red, Near-infrared (NIR), and Shortwave-infrared (SWIR), or NDRII, has been developed to map freshly-opened swiddens in tropical regions. As Red (visible), NIR, and SWIR spectral band combinations (i.e., the VNIR-SWIR spectroscopy) are sensitive to vegetation-moisture variations and thermal anomalies caused by slash and burn in tropical uplands during the dry season, NDRII delineates exact patches of freshly opened swiddens. The latest 20-m map facilitates probing into the landscape patterns of newly opened swiddens and underlines their prevalence in Laos for the first time. Established within the VNIR-SWIR spectroscopy of Sentinel-2 and Landsat-8 Operational Land Imager, the NDRII algorithm contributes to reconstructing historical datasets of tropical swiddens via integrating state-of-the-art approaches that use temporally stacked observations with available VNIR/SWIR satellite imagery and further understanding the dynamics of landscape pattern and disturbance due to rapid transition and transformation.

High SNR eSWIR Image Sensor Applied in Advanced Hyperspectral Imager Aboard China’s GaoFen-5 Satellite and ZY-1 Satellite

This paper presents an extended short-wave infrared (eSWIR) image sensor, a large format infrared focal plane array (IRFPA), applied in advanced hyperspectral imager (AHSI) aboard China’s three GaoFen-5 satellites and two more followed ZY-1 satellites. Hyperspectral imaging has been emerged as a very important application in Earth observation instruments, for the spectral detection provides the spectrum information of ground objects except for the spatial imaging of the objects. AHSI has a 60-km swath width and a 30-m spatial resolution, and has high signal-to-noise ratio (SNR) in spectrum of interest. Large format infrared focal plane arrays which are ordinarily used in staring infrared imaging have some special performance requirements when applied in hyperspectral imaging, such as higher quantum efficiency, lower dark current, lower noise and selectable current conversion gain to match the different radiation flux of different subdivided spectral bands. We developed a format of 2048×512 HgCdTe/Si IRFPA sensor (equivalent 2012×256 after pixel overlapping and binning) in which 2012 pixels meet the demands of 60km swath width and 256 pixels line meet the 200 spectral bands. The sensor has 8-level gains selectable by spectral bands, and array dark current densities on an order of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-10</sup> A/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , quantum efficiency exceeding 80%, and the operability of 99.5% at operating temperature of around 110K. The SNR of this FPA achieved 150 when illuminated under 5×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> photons/pixel.

Accuracy of Bathymetric Depth Change Maps Using Multi-Temporal Images and Machine Learning

Most work to date on satellite-derived bathymetry (SDB) depth change estimates water depth at individual times t1 and t2 using two separate models and then differences the model estimates. An alternative approach is explored in this study: a multi-temporal Sentinel-2 image is created by “stacking” the bands of the times t1 and t2 images, geographically coincident reference data for times t1 and t2 allow for “true” depth change to be calculated for the pixels of the multi-temporal image, and this information is used to fit a single model that estimates depth change directly rather than indirectly as in the model-differencing approach. The multi-temporal image approach reduced the depth change RMSE by about 30%. The machine learning modelling method (categorical boosting) outperformed linear regression. Overfitting of models was limited even for the CatBoost models having the maximum number of variables examined. The visible Sentinel-2 spectral bands contributed most to the model predictions. Though the multi-temporal stacked image approach produced clearly superior depth change estimates compared to the conventional approach, it is limited only to those areas for which geographically coincident multi-temporal reference/“true” depth data exist.

SPTrack: Spectral Similarity Prompt Learning for Hyperspectral Object Tracking

Compared to hyperspectral trackers that adopt the “pre-training then fine-tuning” training paradigm, those using the “pre-training then prompt-tuning” training paradigm can inherit the expressive capabilities of the pre-trained model with fewer training parameters. Existing hyperspectral trackers utilizing prompt learning lack an adequate prompt template design, thus failing to bridge the domain gap between hyperspectral data and pre-trained models. Consequently, their tracking performance suffers. Additionally, these networks have a poor generalization ability and require re-training for the different spectral bands of hyperspectral data, leading to the inefficient use of computational resources. In order to address the aforementioned problems, we propose a spectral similarity prompt learning approach for hyperspectral object tracking (SPTrack). First, we introduce a spectral matching map based on spectral similarity, which converts 3D hyperspectral data with different spectral bands into single-channel hotmaps, thus enabling cross-spectral domain generalization. Then, we design a channel and position attention-based feature complementary prompter to learn blended prompts from spectral matching maps and three-channel images. Extensive experiments are conducted on the HOT2023 and IMEC25 data sets, and SPTrack is found to achieve state-of-the-art performance with minimal computational effort. Additionally, we verify the cross-spectral domain generalization ability of SPTrack on the HOT2023 data set, which includes data from three spectral bands.

Red/near-infrared (NIR) difluoroboron β-diketonate derivatives with reversible mechanochromism for cellular imaging

Near-infrared (NIR) fluorophores have promoted the development of materials for bioimaging, but traditional NIR dyes usually suffer from aggregation-caused quenching (ACQ), impeding their applications. Herein, we propose two difluoroboron β-diketonate complexes TBO and TBS, consisting a donor–acceptor (D-A) structure with triphenylamine (TPA) moiety as an electron donors and difluoroboron as well as furan or thiophene building block as an electron acceptor. The theoretical calculation and optical data shows that both of them have intramolecular charge transfer (ICT) characteristics. Such ICT characteristics endow them with both solvatochromism and dual-state emission (DSE) properties. In the solvent CH2Cl2, the emission wavelength of TBO ranges from 550 nm to 750 nm, with a low fluorescence quantum yield (Φ = 7.0 %). However, in the less polar solvent hexane, the emission wavelength blue-shifts, with an increased Φ reaching up to 18 %. Moreover, TBO and TBS exhibit mechanochromic characteristics and rare multi-channel fluorescence emission phenomena at solid-state. Their solid-state samples can emit fluorescence in four spectral bands with maximum emission wavelengths at 300 nm, 400 nm, 600 nm, and 770 nm under excitation at 240 nm. These unique optical properties are expected to be utilized for detecting polarity of system and deformation. Moreover, according to the results of cell imaging and flow cytometry, TBO molecular were easily internalized into Hela cells and distributed in the cytoplasm with strong red fluorescence. Therefore, this research inspires more insight into development of NIR luminogens for biomedical imaging.

The utilization of blood serum ATR-FTIR spectroscopy for the identification of gastric cancer

Gastric cancer represents a significant public health challenge, necessitating advancements in early diagnostic methodologies. This investigation employed attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy to conduct a multivariate analysis of human serum. The study encompassed the examination of blood samples from 96 individuals diagnosed with gastric cancer and 96 healthy volunteers. Principal component analysis (PCA) was utilized to interpret the infrared spectral data of the serum samples. Specific spectral bands exhibiting intensity variations between the two groups were identified. The infrared spectral ranges of 3500 ~ 3000 cm⁻1, 1700 ~ 1600 cm⁻1, and 1090 ~ 1070 cm⁻1 demonstrated significant diagnostic value for gastric cancer, likely attributable to differences in protein conformation and nucleic acids. By employing machine learning algorithms to differentiate between gastric cancer patients (n = 96) and healthy controls (n = 96), we achieved a sensitivity of up to 89.7% and a specificity of 87.2%. Receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.901. These findings underscore the potential of our serum-based ATR-FTIR spectroscopy examination method as a straightforward, minimally invasive, and reliable diagnostic test for the detection of gastric cancer.

Leveraging deep learning for coastal monitoring: A VGG16-based approach to spectral and textural classification of coastal areas with sentinel-2A data

Coastal ecosystems are vital for the planet's health, providing essential habitats for diverse species and supporting human communities. However, these complex environments face increasing threats from climate change and human activities. Effective monitoring of these areas requires large-scale, efficient, and accurate methods. This study explores the potential of deep learning for automated coastal land cover classification using Sentinel-2A satellite imagery on the Google Earth Engine (GEE) platform. We investigate the impact of transfer learning and spectral band combinations on classification accuracy for five coastal types: artificial, bedrock, sandy, muddy, and vegetation-covered. Our findings demonstrate that a pre-trained VGG16 Convolutional Neural Network (CNN) with transfer learning significantly improves classification accuracy (average 19.3% increase) compared to using default weights. Notably, including the near-infrared (NIR) band in training data leads to superior results, particularly for artificial and bedrock coastlines, where the NIR band's effectiveness in separating land-water boundaries enhances classification accuracy. These results highlight the potential of deep learning for large-scale, automated coastal monitoring, informing applications in sustainable fisheries management, coastal vulnerability assessment, and marine ecosystem conservation.

Carbonyl stretching band in amides as Lorentz oscillator. Insights into anharmonicity and local environment in the liquid phase from NIR and MIR spectra of N-methylformamide and di-N,N-methylformamide

We investigated the anharmonicity and intermolecular interactions of N-methylformamide (NMF) and di-N,N-methylformamide (DMF) in the neat liquid phase with particular interest in the amide bands. The vibrational spectra, complex refractive index, and complex electric permittivity were determined in in the mid- (MIR) and near-infrared (NIR) regions (11,500–560 cm−1; 870–17857 nm). Dispersion analysis was based on the Classical Damped Harmonic Oscillator (CDHO) and simultaneous modelling of the real and imaginary components of the spectra. This data delivered insights into the vibrational energy dissipation and self-association in liquid amides. Identification of the MIR and NIR bands was based on anharmonic GVPT2//B3LYP/6-311++G(d,p) calculations. DMF and NMF follow distinct self-association, evidenced in the MIR fingerprint by the two components of the νCO, the analog of the Amide I band. These conclusions are supported by the structural information derived from the NIR spectra. Furthermore, the contribution of overtones and combination bands in the MIR spectra of amides was examined. The conclusions on molecular interactions and structural dynamics of NMF and DMF contribute to a deeper understanding of the effects of changes in the local environment of the amide group.

Mapping the dynamics of aquatic vegetation in Lake Kyoga and its linkages to satellite lakes

Lake Kyoga is a shallow, young, flooded basin just north of and about 30m lower than Lake Victoria. The catchment encompasses Lake Kyoga itself, and a constellation of several dozen small satellite lakes following valley contours mostly to its east. The Kyoga basin fish fauna shares many non-cichlid species plus a spectacular, partially endemic radiation of haplochromine cichlids most similar to but still largely distinct from those in Lake Victoria. This fish fauna is of high conservation concern, as it preserves remnants of the regional species flock that have disappeared from Lake Victoria and Lake Kyoga, leaving small remnant populations in some of the satellite lakes. Now, these too are imperiled by limnological dynamics, including fluctuations in the nature and extent of aquatic vegetation. The water bodies in the Kyoga Basin are highly dynamic due both to fluctuation in water level and large amplitude variation in marginal and floating vegetation. This variation has profound evolutionary and conservation implications, since it can create and destroy critical aquatic habitat. It can also alternately anneal and cleave gene flow over time, both between the main lake and its satellites, and among the satellite lakes. The aquatic vegetation cluttering these linkages can create a spatial refugium for many native fish species that are more tolerant of hypoxia than an introduced macropredator, the Nile perch. Anthropogenic impacts to this region have greatly increased in recent years, altering relationships between aquatic vegetation and endangered species, fisheries and other ecosystem services provided by the lake. Understanding these dynamics require a means of mapping aquatic vegetation, connectivity, and habitat through time. Here we develop a new and improved algorithm to map the spatial distribution and dynamics of floating and emergent aquatic vegetation via remote sensing. We utilize a time series of 440 Landsat images dating from 1986 to 2020. A series of water and vegetation indices are designed to reveal change in the aquascape over time. First, two types of water masks are derived using a majority rule - a separate water mask for each image and a composite water mask of the region over the study period. Second, the difference between the two masks is then used to delineate the potential location of macrophytes over the image. Third, an algorithm is developed to separate the floating vegetation from emergent vegetation; this algorithm uses Landsat spectral bands and two additional spatial and temporal metrics that considerably improve classification accuracy. A more extensive analysis of aquascape trajectories using remote sensing can inform fish conservation strategies and fisheries management and illuminate the role of landscape dynamics in macroevolutionary patterns of aquatic taxa.

Spectroscopic and computational investigations of isostructural phase transitions in urea 4-carboxyanilinium nitrate having trapped disordered-nitrate ions

Urea 4-carboxyanilinium nitrate (U4-CAN) and its functional groups deuterated counterpart dU4-CAN were studied using infrared vibrational spectroscopy and computational analysis. Using the known frequencies of the parent components the infrared vibrational frequencies of U4-CAN and dU4-CAN were assigned. FTIR study was carried out to understand how the intra-and inter-molecular interactions in the parent components are affected by U4-CAN co-crystal formation. U4-CAN undergoes isostructural phase transition at 359.1 K. Hence FTIR spectra of U4-CAN were also recorded at different temperature in the range 293 K to 368 K. The interesting observation seen with temperature dependent spectra was:(i) the spectral band intensity increased with increasing temperature and (ii) the peak position of almost all bands did not change in the entire temperature range studied. This results corroborate with the reported structural data of U4-CAN were in it is found that the structural phase transition is isostructural. Hence the crystal structure in the range 293 K to 368 K has same space group and differ only in few hydrogen bond interactions. In order to carry out various theoretical calculation of U4-CAN, the crystallographically obtained structure at 293 K was optimized by density functional theory (DFT) with B3LYP/6–311 G basis set. The theoretical calculated vibration spectra were similar to the experimentally obtained FTIR data. The fingerprint plot of U4-CAN obtained using CrystalExplorer 21 software indicated that the most prominent interaction corresponds to the short O···H contact. Noncovalent interaction (NCL) study indicated that the U4-CAN complex has steric, van der Waals and hydrogen bond interactions and the NH⋅⋅⋅⋅⋅O hydrogen bond interaction between NH3+/ NH2 moieties and NO3- was the strongest. From QTAIM calculation the strongest hydrogen bond interaction in U4-CAN complex was for NH.....O and NH.....N interactions.

UAV hyperspectral image acquisition and processing, an application for nutrient estimation of rice in Vietnam

Hyperspectral imagery obtained from Unmanned Aerial Vehicles (UAVs) is increasingly employed to investigate nutrient concentrations in vegetation. The deployment of a hyperspectral camera on a UAV, flight planning, image acquisition, preprocessing of hyperspectral data, and the subsequent estimation of nutrient concentrations in vegetation are facing challenges. These challenges manifest as geometric, spectral distortions, and the abundance of numerous spectral bands. This study seeks to guide on mitigating the impact of issues encountered during an experiment to estimate nutrient concentrations in rice leaves using UAV hyperspectral images. An industrial hexagonal drone equipped with a push-broom hyperspectral camera featuring 122 bands within the Visible to Near-Infrared (VIS-NIR) wavelength range (400-960 nm) is employed to collect data over a 1-hectare testing rice field. Models for estimating Leaf Phosphorus Concentration (LPC) and Leaf Potassium Concentration (LKC) are developed based on the correlation between hyperspectral images, characterized by a 3 cm spatial resolution, and 162 LPC and 162 LKC reference data points. Utilizing various vegetation indices for LPC and LKC estimation, the outcomes reveal that a combination of band wavelengths at 838 nm and 734 nm is effective for LPC estimation, yielding a Root Mean Square Error (RMSE) of 27.1%. Conversely, LKC estimation exhibits an RMSE of 38.8% with an insignificant correlation between LKC and the current wavelength ranges. Above all, this study is a primary example of the utilization of UAV hyperspectral data in precision agriculture in Vietnam.

Neotectonic indications of Al-Shihaby fan on Iraqi-Iranian borders

Al-Shihaby alluvial fan is considered a significant and major geomorphologic phenomenon that evolved on the east side of Mesopotamia. It is located in the Wasit Governorate, near the Iraqi-Iranian borders. The fandom's dominant trend is southwest-northeast. This study aims to enhance our understanding of the indications and continuity of the fan's neotectonic activity. To reach this aim, we used software such as Arc GIS, Global Mapper, and Surfer, in addition to using data from USGS to identify the stages of the fan. A merging of spectral bands (composite bands), a contour map, and longitudinal and transverse topographic sections were done to analyze and interpret the neotectonics of the study area. This study concluded that the fan has passed through five stages in different periods and that its continuation to the present indicates that the fan is still active. These five stages recognized within the fan belong to the Pliocene- Late Pleistocene age range. Each stage is a breakpoint in sedimentation, and when tectonic activity occurs, the next stage begins. Besides that, the study concludes that the elevation range of the area from the cross sections is from 15 m in the southwest of the area to 120 m in the northeast above sea level from the elevation map derived from the DEM file. Besides that, the increase in sediment thickness on the western side of the fan compared to the eastern side, which belongs to the streams on the west side of the fan, in addition to the deposition of the alluvial fan, was related to the Mandali-Badra-Amara Faults (Zagros Front Fault (ZFF)) and its activity, as well as the relative uplifting of the Hemrin structure versus the subsidence of the Mesopotamia Plain.